The idea is to make pluggable pydantic models where other libs can have config within a libraries config, and be type checked.

dynamic_pydantic_models.py

from datetime import datetime
from typing import List, Optional

from pydantic import BaseModel, create_model, validator
import toml


class User(BaseModel):
    id: int
    name = "John Doe"
    signup_ts: Optional[datetime] = None
    friends: List[int] = []

    @validator("name")
    def name_must_contain_space(cls, v):
        if " " not in v:
            raise ValueError("must contain a space")
        return v.title()


class Load(BaseModel):
    plugin_id: int = 5
    name: str = "Plugin"


class LoadPlugin(BaseModel):
    # defaults to Load() if it is missing from the config, all values in Load
    # must have a default, but does not require user to have a [load] key in
    # config
    load: Load = Load()


class UserPlugin(BaseModel):
    # User has required keys, so you cannot set a default and the user must
    # have a [user] key with at least an id in it.
    user: User


plugins = (
    UserPlugin,
    LoadPlugin,
)

DynamicUser = create_model("DynamicUser", __base__=plugins)


def make_user():
    external_data = toml.loads(
        """
        [user]
        id='123'
        name='waylon walker' # this will fail name_must_contain_space
        """
    )
    user = DynamicUser(**external_data)
    return user